The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Using support vector machine with a hybrid feature selection method to the stock trend prediction
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In the citing paper
“Due to their ability to recognize patterns in nonlinear, dynamic time series data (Chang et al., 2009; Lee, 2009; Żbikowski, 2015), these methods are especially popular in financial market forecasting.”
From Bridging the divide in financial market forecasting: machine learners vs. financial economists (2016) · cites this paper as Lee, 2009
Citations
Cites
The Nature of Statistical Learning Theory
Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138
Wrappers for feature subset selection
Kohavi, R., & John, G. H. (1997) · Artificial Intelligence · doi:10.1016/s0004-3702(97)00043-x · Cited by 9,096
A Practical Guide to Support Vector Classication
Hsu, C., Chang, C.-C., & Lin, C. (2008) · Cited by 5,056
An Introduction to Support Vector Machines
Cristianini, N., & Shawe-Taylor, J. S. (2000) · ePrints Soton (University of Southampton) · Cited by 4,115
Feature selection for high-dimensional data: a fast correlation-based filter solution
Yu, L., & Liu, H. (2003) · Cited by 2,305
Financial time series forecasting using support vector machines
Kim, K.-J. (2003) · Neurocomputing · doi:10.1016/s0925-2312(03)00372-2 · Cited by 1,734
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
Hall, M. A. (2000) · Cited by 1,713
Interpreting neural-network connection weights
Garson, G. D. (1991) · AI Expert archive · doi:10.5555/129449.129452 · Cited by 1,498
Application of support vector machines in financial time series forecasting
Tay, F. E. H., & Cao, L. (2001) · Omega · doi:10.1016/s0305-0483(01)00026-3 · Cited by 1,274
Efficient Analytic Approximation of American Option Values
Barone‐Adesi, G., & Whaley, R. E. (1987) · The Journal of Finance · doi:10.1111/j.1540-6261.1987.tb02569.x · Cited by 1,130
Research works printed but not linked: 2
- TEJD. (2008). Taiwan economic journal database. Available form <http://61.30.108.162/image/readme1.htm>.
- Weigend, A., (1994). On overfitting and the effective number of hidden units. In Proceedings of the 1993 connectionist models summer school (pp. 335–3420).
Cited by
Sorted by citations
Items 301–303 of 303
Comprehensive Approach to Feature Selection
Njoku, U. F., Abelló, A., Bilalli, B., & Bontempi, G. (2026) · Springer eBooks · doi:10.1007/978-3-032-18765-9_4
A, S. H., Yashpal Gupta, S., Gupta, H., Dwivedi, H., Chouhan, D., & Kumari, P. (2026) · International Conference on Inventive Computing and Informatics (ICICI) · doi:10.1109/icici68773.2026.11580875
Forecasting Stock Price Index Using Multiple Linear Regression Model
Krishnamoorthy, S., & Jaganathan, B. (2026) · Springer proceedings in mathematics & statistics · doi:10.1007/978-981-95-5891-9_45
Metadata
- Authors
- Lee, M.-C.
- Affiliations
- National Pingtung University (TW)
- Corresponding author
- Lee, Ming-Chi
- ORCID
- Lee, Ming-Chi
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2009-10
- Volume
- 36
- Issue
- 8
- Pages
- 10896-10904
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2091621250
- Cited by
- 302
- References
- 34
- Citations by year
- 2026: 11 · 2025: 12 · 2024: 17 · 2023: 29 · 2022: 32 · 2021: 24 · 2020: 29 · 2019: 26 · 2018: 15 · 2017: 12 · 2016: 15 · 2015: 14 · 2014: 20 · 2013: 15 · 2012: 11
- FWCI
- 14.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Expert Systems with Applications (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Stock Market Forecasting Methods
- Physical Sciences › Computer Science › Signal Processing › Time Series Analysis and Forecasting
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Keywords
- stock trend prediction, support vector machine, hybrid feature selection, F-score, sequential floating forward selection, filter and wrapper methods, feature selection, back propagation neural network comparison, kernel parameter optimization, financial time series
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